Abstract
Computer assisted on-line monitoring and diagnosis is becoming an increasingly important part of modern process control systems. Diagnosis systems can be built from two different main principles: symptom-based diagnosis and model-based diagnosis. A symptom-based system aims at explicitly associate the symptoms of a fault, as indicated by the sensors, with the fault itself. The associations can be expressed as rules, tables, etc. The source of the diagnosis knowledge is experienced “expert” operators. Experience has shown that a purely heuristic approach like this has several drawbacks: knowledge acquisition difficulties, problems with completeness, unability to handle problems for which the experts have no solution, etc.
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© 1995 Springer Science+Business Media Dordrecht
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Årzen, KE., Wallén, A., Petti, T.F. (1995). Model-Based Diagnosis: State Transition Events and Constraint Equations. In: Tzafestas, S.G., Verbruggen, H.B. (eds) Artificial Intelligence in Industrial Decision Making, Control and Automation. Microprocessor-Based and Intelligent Systems Engineering, vol 14. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-0305-3_16
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DOI: https://doi.org/10.1007/978-94-011-0305-3_16
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